A question-answering framework for automated abstract screening using large language models.

Journal: Journal of the American Medical Informatics Association : JAMIA

PMID: 39042516

Abstract

OBJECTIVE: This paper aims to address the challenges in abstract screening within systematic reviews (SR) by leveraging the zero-shot capabilities of large language models (LLMs).

Authors

Opeoluwa Akinseloyin

Centre for Computational Science and Mathematical Modelling, Coventry University, Coventry CV1 2TT, United Kingdom.
Xiaorui Jiang

Information School, The University of Sheffield, Sheffield S10 2AH, United Kingdom.
Vasile Palade

Centre for Data Science, Coventry University, Coventry, United Kingdom. Electronic address: vasile.palade@coventry.ac.uk.

Keywords

Abstracting and Indexing Artificial Intelligence Humans Information Storage and Retrieval Natural Language Processing Systematic Reviews as Topic

External Resources

View on PubMed Access via DOI PubMed (39042516)

A question-answering framework for automated abstract screening using large language models.

Abstract

Authors

Keywords

External Resources

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